We are data-driven investors.

Our tools consist of proprietary algorithms that add value at every step of the investment cycle. 

Signal building

Each of our alpha signals must compete against existing research and a rigorous testing cycle. Only when we can identify an advantage does the signal find its way into the portfolio.

Sub-strategy portfolios

We think in terms of a variety of strategies, which can exploiting different investment styles. Since each of these signals has its own specific characteristics, we aggregate the signals across many assets into a sub-strategy.

Meta portfolio

Our meta portfolio is aggregated based on the movement patterns of the sub-strategy portfolios. The meta portfolio is constantly reassembled in order to optimally exploit the different behaviors of the sub-strategies.

Trading cost reduction

The use of various statistical tools and machine learning, allow us to implement strategies even when high turnover occurs. We also view cost reduction as an alpha component.

We are asset class agnostic. Furthermore, we classify each tradable instrument based on its characteristics and consider it with similar assets in a group. By constantly revaluing asset groups, we can reliably anticipate structural changes. In this way, we maintain maximum diversification potential at all times.

Our quality assurance is at the core of our beliefs. Every assumption, every signal and every portfolio, must stand up to a series of validation mechanisms that include the largest possible number of historical regimes and structural breaks. To test the unprecedented as well, we synthetically generate time series that contain as yet unknown but imaginable regimes and correlations. In this way, we create models that can be trusted.